{"id":2916784,"url":"https://alion.io/job/veraxion-azure-data-engineer-geospatial","title":"Azure Data Engineer (Geospatial)","company":{"id":722518,"name":"Veraxion","domain":"veraxion.com","url":"https://alion.io/company/veraxion","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":71},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Airflow","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-20T10:35:30Z","employer_posted_date":null,"last_verified_at":"2026-10-20T10:35:30Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"We are looking for an experienced Data Engineer with strong hands-on expertise in Python, SQL, Spark/PySpark, and geospatial data processing to build and maintain scalable, production-grade data pipelines. You will work closely with Data Scientists, Analysts, and Engineering teams to build reliable data platforms and prepare high-quality datasets for analytics and downstream applications.\n\nResponsibilities: \nDesign, build, and maintain scalable ETL/ELT data pipelines using Python, SQL, and Spark/PySpark.\nProcess and transform large-scale geospatial and non-geospatial datasets from multiple sources.\nWork extensively with latitude/longitude, GPS, coordinates, maps, location data, and spatial datasets.\nPerform geospatial data processing and analysis, including spatial joins, Proximity analysis, Distance calculations, Location-based aggregations, and coordinate and location transformations.\nIntegrate geospatial data with structured and unstructured data sources.\nBuild and optimise data pipelines for performance, reliability, scalability, and maintainability.\nDevelop cloud-based data solutions using Azure.\nWork with data lakes, data warehouses, distributed processing frameworks, and modern data architectures.\nImplement workflow orchestration using tools such as Apache Airflow and Azure Data Factory.\nImplement data quality checks, testing, monitoring, and pipeline observability.\nTroubleshoot pipeline failures, data inconsistencies, and performance issues.\nCollaborate with Data Scientists, Data Analysts, and Engineering teams to prepare high-quality datasets for analytics and downstream applications.\nFollow best practices around data security, governance, deployment, and production operations.\nParticipate in Agile development practices, code reviews, and technical discussions.\n\nRequirements: \n5-10 years of experience in Data Engineering or a closely related role.\nStrong hands-on experience with Python and SQL for data processing and pipeline development.\nExperience working with geospatial/location datasets, coordinates, latitude/longitude, GPS, maps, satellite imagery, spatial datasets, etc.\nHands-on experience with Apache Spark/PySpark for processing large-scale datasets.\nHands-on experience working with geospatial/spatial data is mandatory.\nExperience building and maintaining production-grade ETL/ELT data pipelines.\nExperience with at least one major cloud platform, Azure.\nGood understanding of data lakes, data warehouses, distributed data processing, and modern data architectures.\nExperience with workflow orchestration tools such as Azure Data Factory\nUnderstanding of data quality, testing, monitoring, security, and governance practices.\nStrong problem-solving and communication skills, with the ability to work effectively in an Agile engineering environment.\nIn terms of geospatial data, experience should include latitude/longitude and maps.\nSkills\nData Engineering, ETL, Spark, SQL, Azure Data Factory, Python, Azure, Azure Data Lake, GPS, GPS 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